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#516: Accelerating Python Data Science at NVIDIA

Talk Python To Me

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Leveraging GPUs in Data Science

This chapter explores the complexities and benefits of using GPUs for concurrent jobs in data science, particularly through the lens of the Dask library and its integration with technologies like Rapids. The discussion includes performance trade-offs, error management, and the importance of optimizing memory usage when handling large datasets. It also highlights advancements in tools for machine learning, the significance of vector databases, and the evolving landscape of software architectures in response to new hardware capabilities.

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